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Parameters Estimation of Ultrasonics Echoes using the Cuckoo Search and Adaptive Cuckoo Search Algorithms

机译:使用杜鹃搜索和自适应杜鹃搜索算法的超声波回声的参数估计

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In this study we present a novel approach to estimate ultrasonic echo pattern using the two algorithms: Cuckoo Search (CS) and Adaptive Cuckoo Search (ACS). We model ultrasonic backscattered echoes in terms of superimposed Gaussian echoes corrupted by noise. Each Gaussian echo in the model is a non linear function of a set of parameters: echo bandwidth, arrival time, center frequency, amplitude and phase. The estimation of parameters is formulated as a nonlinear optimisation problem. Simulations are carried out to assess the performance of the proposed algorithms. Finally the algorithms were applied on experimental data for thickness measurement. The CS algorithm converges to best solution with less time than ACS. However, ACS algorithm outperforms CS.
机译:在这项研究中,我们介绍了一种使用这两种算法来估计超声回声模式的新方法:杜鹃搜索(CS)和自适应咕咕搜索(ACS)。我们模拟超声波背散射回声,以噪音损坏的叠加高斯回声。该模型中的每个高斯回声都是一组参数的非线性函数:回波带宽,到达时间,中心频率,幅度和相位。参数的估计被制定为非线性优化问题。进行仿真以评估所提出的算法的性能。最后,算法应用于用于厚度测量的实验数据。 CS算法将收敛到最佳解决方案,而不是ACS的时间较少。但是,ACS算法优于CS。

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